The use of antibodies as therapeutic agents has gained increasing acceptance over the last several years, and there are currently 18 FDA-approved monoclonal antibody therapies. The main advantages of antibody-based therapy over traditional, small molecule approaches are: more rapid development times; lower toxicity; ability to disrupt protein-protein interactions. The success of this approach has been the development of methods for reducing the immunogenicity of antibodies administered to patients. Such methods generally rely on the ability to screen through large numbers of human or humanized antibody candidates. Display systems offer the most efficient mechanism for identifying rare, high affinity members of such antibody libraries. The effectiveness of currently available display systems (phage display, ribosome display, and yeast display), however, is limited by strong selection biases between library members that do not translate to improved antibody affinity. Such biases include differences in heavy and light chain expression levels and/or secretion efficiency, differences in stability/dimerization of scFv's, and differences from avidity effects. The object of this grant is to develop a novel display system that overcomes all of these biases and provides a robust and efficient method for identifying high affinity and specificity human or humanized antibodies against nearly any therapeutic target.